Tommy Wood

NBT’s Tommy Wood on engineering sustained health using A.I. & standard blood chemistry

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In this sixth episode, Tommy Wood, Chief Scientific Officer of Nourish Balance Thrive, explains that the majority of modern disease is caused by our environment and as such, under our control. He shares his experience that A.I. coupled with ordinary blood tests, can inform us of changes we can make to protect/optimize our health, or when sick, lower the cost by predicting which further tests to conduct.

Topics we discussed in this episode
  • Most chronic disease (e.g. diabetes, Alzheimer’s, arthritis, certain cancers) we could eliminate by controlling our environment (e.g. diet, sleep, toxic exposures)
  • Sustaining long-term health by preventing, or slowing down the aging processes
  • Predicting chronic disease based upon subjective quality of life questionnaires or with the inclusion of simple blood tests, processed by machine learning algorithms
  • Prediction of biological age based upon simple blood tests, processed by machine learning algorithms
  • Personalizing lifestyle interventions to achieve longer health and life spans, using only simple blood chemistry processed with machine learning
  • Nourish Balance Thrive’s Blood Chemistry Calculator
  • Nourish Balance Thrive’s Elite Performance Analysis Tool
  • Laboratory biomarker ranges are averages derived from a sick population rather than a healthy nor optimized health population
  • Predicting where an individual’s health may be further optimized (e.g. nutrient deficiencies, heavy metal loads, hormone levels) using only cheap blood tests processed by machine learning algorithms
  • Humans (e.g. doctors) would be unable to see valuable patterns in cheap blood test data
  • Lack of biological data derived from healthy individuals, masses of data derived from sick individuals
  • Groups working on health optimization as opposed to orthodox healthcare’s focus on sick care
  • Non-pathological insulin resistance, physiological insulin resistance
  • Elevated fasting glucose and predicted biological age
  • Genomics can’t optimize an individual’s diet and lifestyle, at least at present
  • An individual’s diet and lifestyle can be optimized today through subjective questionnaires and simple blood chemistry processed by machine learning algorithms
  • Most chronic disease is a metabolic disease
  • Ancestral health approach prevents or even reverses chronic disease; advanced technologies not needed
  • Digital phenotyping
  • Need to filter tap water and other environmental controls to protect our health span
  • The likelihood that most of the healthy population is in fact not “healthy”; the bar of “healthy” has been lowered so people don’t know of a “more well”
  • Gut issues underlie or contribute to many health issues we see today
  • Building tools that can track underlying trends or patterns in our blood biochemistry so that we can know if lifestyle interventions are working for us
  • Nutritional epidemiology is a broken science
  • Democratizing functional medicine
  • Engineering sustained health
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